mirror of
https://github.com/prometheus/prometheus
synced 2025-04-01 14:48:52 +00:00
Merge pull request #277 from prometheus/feature/exporter-prefix
Prepend "exporter_" to labels that already exist in exported metrics.
This commit is contained in:
juliusv
commit
97736a030a
@ -20,6 +20,9 @@ const (
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JobLabel = LabelName("job")
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// The label name indicating the instance from which a timeseries was scraped.
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InstanceLabel = LabelName("instance")
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// The label name prefix to prepend if a synthetic label is already present
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// in the exported metrics.
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ExporterLabelPrefix = LabelName("exporter_")
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// The metric name for the synthetic health variable.
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ScrapeHealthMetricName = LabelValue("up")
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// The metric name for synthetic alert timeseries.
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0
retrieval/format/fixtures/empty.json
Normal file
0
retrieval/format/fixtures/empty.json
Normal file
79
retrieval/format/fixtures/test0_0_1-0_0_2.json
Normal file
79
retrieval/format/fixtures/test0_0_1-0_0_2.json
Normal file
@ -0,0 +1,79 @@
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[
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{
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"baseLabels": {
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"name": "rpc_calls_total",
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"job": "batch_job"
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},
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"docstring": "RPC calls.",
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"metric": {
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"type": "counter",
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"value": [
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{
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"labels": {
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"service": "zed"
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},
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"value": 25
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},
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{
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"labels": {
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"service": "bar"
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},
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"value": 25
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},
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{
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"labels": {
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"service": "foo"
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},
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"value": 25
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}
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]
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}
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},
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{
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"baseLabels": {
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"name": "rpc_latency_microseconds"
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},
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"docstring": "RPC latency.",
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"metric": {
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"type": "histogram",
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"value": [
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{
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"labels": {
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"service": "foo"
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},
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"value": {
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"0.010000": 15.890724674774395,
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"0.050000": 15.890724674774395,
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"0.500000": 84.63044031436561,
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"0.900000": 160.21100853053224,
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"0.990000": 172.49828748957728
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}
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},
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{
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"labels": {
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"service": "zed"
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},
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"value": {
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"0.010000": 0.0459814091918713,
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"0.050000": 0.0459814091918713,
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"0.500000": 0.6120456642749681,
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"0.900000": 1.355915069887731,
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"0.990000": 1.772733213161236
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}
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},
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{
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"labels": {
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"service": "bar"
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},
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"value": {
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"0.010000": 78.48563317257356,
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"0.050000": 78.48563317257356,
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"0.500000": 97.31798360385088,
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"0.900000": 109.89202084295582,
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"0.990000": 109.99626121011262
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}
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}
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]
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}
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}
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]
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@ -47,3 +47,24 @@ func LabelSet(labels map[string]string) model.LabelSet {
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return labelset
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}
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// Helper function to merge a target's base labels ontop of the labels of an
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// exported sample. If a label is already defined in the exported sample, we
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// assume that we are scraping an intermediate exporter and attach
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// "exporter_"-prefixes to Prometheus' own base labels.
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func mergeTargetLabels(entityLabels, targetLabels model.LabelSet) model.LabelSet {
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result := model.LabelSet{}
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for label, value := range entityLabels {
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result[label] = value
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}
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for label, labelValue := range targetLabels {
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if _, exists := result[label]; exists {
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result[model.ExporterLabelPrefix+label] = labelValue
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} else {
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result[label] = labelValue
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}
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}
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return result
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}
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@ -77,18 +77,8 @@ func (p *processor001) Process(stream io.ReadCloser, timestamp time.Time, baseLa
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pendingSamples := model.Samples{}
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for _, entity := range entities {
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for _, value := range entity.Metric.Value {
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metric := model.Metric{}
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for label, labelValue := range baseLabels {
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metric[label] = labelValue
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}
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for label, labelValue := range entity.BaseLabels {
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metric[model.LabelName(label)] = model.LabelValue(labelValue)
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}
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for label, labelValue := range value.Labels {
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metric[model.LabelName(label)] = model.LabelValue(labelValue)
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}
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entityLabels := LabelSet(entity.BaseLabels).Merge(LabelSet(value.Labels))
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labels := mergeTargetLabels(entityLabels, baseLabels)
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switch entity.Metric.MetricType {
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case gauge001, counter001:
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@ -100,7 +90,7 @@ func (p *processor001) Process(stream io.ReadCloser, timestamp time.Time, baseLa
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}
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pendingSamples = append(pendingSamples, model.Sample{
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Metric: metric,
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Metric: model.Metric(labels),
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Timestamp: timestamp,
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Value: model.SampleValue(sampleValue),
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})
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@ -123,16 +113,16 @@ func (p *processor001) Process(stream io.ReadCloser, timestamp time.Time, baseLa
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continue
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}
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childMetric := make(map[model.LabelName]model.LabelValue, len(metric)+1)
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childMetric := make(map[model.LabelName]model.LabelValue, len(labels)+1)
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for k, v := range metric {
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for k, v := range labels {
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childMetric[k] = v
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}
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childMetric[model.LabelName(percentile001)] = model.LabelValue(percentile)
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pendingSamples = append(pendingSamples, model.Sample{
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Metric: childMetric,
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Metric: model.Metric(childMetric),
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Timestamp: timestamp,
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Value: model.SampleValue(individualValue),
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})
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@ -18,99 +18,104 @@ import (
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"fmt"
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"github.com/prometheus/prometheus/model"
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"github.com/prometheus/prometheus/utility/test"
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"io/ioutil"
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"strings"
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"os"
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"path"
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"testing"
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"time"
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)
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func testProcessor001Process(t test.Tester) {
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var scenarios = []struct {
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in string
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out model.Samples
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err error
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in string
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baseLabels model.LabelSet
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out model.Samples
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err error
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}{
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{
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in: "empty.json",
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err: fmt.Errorf("unexpected end of JSON input"),
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},
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{
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in: `[{"baseLabels":{"name":"rpc_calls_total"},"docstring":"RPC calls.","metric":{"type":"counter","value":[{"labels":{"service":"zed"},"value":25},{"labels":{"service":"bar"},"value":25},{"labels":{"service":"foo"},"value":25}]}},{"baseLabels":{"name":"rpc_latency_microseconds"},"docstring":"RPC latency.","metric":{"type":"histogram","value":[{"labels":{"service":"foo"},"value":{"0.010000":15.890724674774395,"0.050000":15.890724674774395,"0.500000":84.63044031436561,"0.900000":160.21100853053224,"0.990000":172.49828748957728}},{"labels":{"service":"zed"},"value":{"0.010000":0.0459814091918713,"0.050000":0.0459814091918713,"0.500000":0.6120456642749681,"0.900000":1.355915069887731,"0.990000":1.772733213161236}},{"labels":{"service":"bar"},"value":{"0.010000":78.48563317257356,"0.050000":78.48563317257356,"0.500000":97.31798360385088,"0.900000":109.89202084295582,"0.990000":109.99626121011262}}]}}]`,
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in: "test0_0_1-0_0_2.json",
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baseLabels: model.LabelSet{
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model.JobLabel: "batch_exporter",
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},
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out: model.Samples{
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model.Sample{
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Metric: model.Metric{"service": "zed", model.MetricNameLabel: "rpc_calls_total"},
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Metric: model.Metric{"service": "zed", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job", "exporter_job": "batch_exporter"},
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Value: 25,
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},
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model.Sample{
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Metric: model.Metric{"service": "bar", model.MetricNameLabel: "rpc_calls_total"},
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Metric: model.Metric{"service": "bar", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job", "exporter_job": "batch_exporter"},
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Value: 25,
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},
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model.Sample{
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Metric: model.Metric{"service": "foo", model.MetricNameLabel: "rpc_calls_total"},
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Metric: model.Metric{"service": "foo", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job", "exporter_job": "batch_exporter"},
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Value: 25,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
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Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed", "job": "batch_exporter"},
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Value: 0.0459814091918713,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
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Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar", "job": "batch_exporter"},
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Value: 78.48563317257356,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
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Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo", "job": "batch_exporter"},
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Value: 15.890724674774395,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
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Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed", "job": "batch_exporter"},
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Value: 0.0459814091918713,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
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Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar", "job": "batch_exporter"},
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Value: 78.48563317257356,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
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Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo", "job": "batch_exporter"},
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Value: 15.890724674774395,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
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Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed", "job": "batch_exporter"},
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Value: 0.6120456642749681,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
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Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar", "job": "batch_exporter"},
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Value: 97.31798360385088,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
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Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo", "job": "batch_exporter"},
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Value: 84.63044031436561,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
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Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed", "job": "batch_exporter"},
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Value: 1.355915069887731,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
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Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar", "job": "batch_exporter"},
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Value: 109.89202084295582,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
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Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo", "job": "batch_exporter"},
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Value: 160.21100853053224,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
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Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed", "job": "batch_exporter"},
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Value: 1.772733213161236,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
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Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar", "job": "batch_exporter"},
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Value: 109.99626121011262,
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},
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model.Sample{
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Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
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Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo", "job": "batch_exporter"},
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Value: 172.49828748957728,
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},
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},
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@ -124,9 +129,12 @@ func testProcessor001Process(t test.Tester) {
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close(c)
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}(inputChannel)
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reader := strings.NewReader(scenario.in)
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reader, err := os.Open(path.Join("fixtures", scenario.in))
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if err != nil {
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t.Fatalf("%d. couldn't open scenario input file %s: %s", scenario.in, err)
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}
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err := Processor001.Process(ioutil.NopCloser(reader), time.Now(), model.LabelSet{}, inputChannel)
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err = Processor001.Process(reader, time.Now(), scenario.baseLabels, inputChannel)
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if !test.ErrorEqual(scenario.err, err) {
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t.Errorf("%d. expected err of %s, got %s", i, scenario.err, err)
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continue
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@ -53,8 +53,6 @@ var Processor002 ProcessorFunc = func(stream io.ReadCloser, timestamp time.Time,
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|
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pendingSamples := model.Samples{}
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for _, entity := range entities {
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entityLabels := baseLabels.Merge(LabelSet(entity.BaseLabels))
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switch entity.Metric.Type {
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case "counter", "gauge":
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var values []counter
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@ -67,7 +65,8 @@ var Processor002 ProcessorFunc = func(stream io.ReadCloser, timestamp time.Time,
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}
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for _, counter := range values {
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labels := entityLabels.Merge(LabelSet(counter.Labels))
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entityLabels := LabelSet(entity.BaseLabels).Merge(LabelSet(counter.Labels))
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labels := mergeTargetLabels(entityLabels, baseLabels)
|
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|
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pendingSamples = append(pendingSamples, model.Sample{
|
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Metric: model.Metric(labels),
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@ -88,8 +87,9 @@ var Processor002 ProcessorFunc = func(stream io.ReadCloser, timestamp time.Time,
|
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|
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for _, histogram := range values {
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for percentile, value := range histogram.Values {
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labels := entityLabels.Merge(LabelSet(histogram.Labels))
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labels[model.LabelName("percentile")] = model.LabelValue(percentile)
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entityLabels := LabelSet(entity.BaseLabels).Merge(LabelSet(histogram.Labels))
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entityLabels[model.LabelName("percentile")] = model.LabelValue(percentile)
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labels := mergeTargetLabels(entityLabels, baseLabels)
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pendingSamples = append(pendingSamples, model.Sample{
|
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Metric: model.Metric(labels),
|
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|
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@ -18,99 +18,104 @@ import (
|
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"fmt"
|
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"github.com/prometheus/prometheus/model"
|
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"github.com/prometheus/prometheus/utility/test"
|
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"io/ioutil"
|
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"strings"
|
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"os"
|
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"path"
|
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"testing"
|
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"time"
|
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)
|
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|
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func testProcessor002Process(t test.Tester) {
|
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var scenarios = []struct {
|
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in string
|
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out model.Samples
|
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err error
|
||||
in string
|
||||
baseLabels model.LabelSet
|
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out model.Samples
|
||||
err error
|
||||
}{
|
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{
|
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in: "empty.json",
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err: fmt.Errorf("EOF"),
|
||||
},
|
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{
|
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in: `[{"baseLabels":{"name":"rpc_calls_total"},"docstring":"RPC calls.","metric":{"type":"counter","value":[{"labels":{"service":"zed"},"value":25},{"labels":{"service":"bar"},"value":25},{"labels":{"service":"foo"},"value":25}]}},{"baseLabels":{"name":"rpc_latency_microseconds"},"docstring":"RPC latency.","metric":{"type":"histogram","value":[{"labels":{"service":"foo"},"value":{"0.010000":15.890724674774395,"0.050000":15.890724674774395,"0.500000":84.63044031436561,"0.900000":160.21100853053224,"0.990000":172.49828748957728}},{"labels":{"service":"zed"},"value":{"0.010000":0.0459814091918713,"0.050000":0.0459814091918713,"0.500000":0.6120456642749681,"0.900000":1.355915069887731,"0.990000":1.772733213161236}},{"labels":{"service":"bar"},"value":{"0.010000":78.48563317257356,"0.050000":78.48563317257356,"0.500000":97.31798360385088,"0.900000":109.89202084295582,"0.990000":109.99626121011262}}]}}]`,
|
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in: "test0_0_1-0_0_2.json",
|
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baseLabels: model.LabelSet{
|
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model.JobLabel: "batch_exporter",
|
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},
|
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out: model.Samples{
|
||||
model.Sample{
|
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Metric: model.Metric{"service": "zed", model.MetricNameLabel: "rpc_calls_total"},
|
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Metric: model.Metric{"service": "zed", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job", "exporter_job": "batch_exporter"},
|
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Value: 25,
|
||||
},
|
||||
model.Sample{
|
||||
Metric: model.Metric{"service": "bar", model.MetricNameLabel: "rpc_calls_total"},
|
||||
Metric: model.Metric{"service": "bar", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job", "exporter_job": "batch_exporter"},
|
||||
Value: 25,
|
||||
},
|
||||
model.Sample{
|
||||
Metric: model.Metric{"service": "foo", model.MetricNameLabel: "rpc_calls_total"},
|
||||
Metric: model.Metric{"service": "foo", model.MetricNameLabel: "rpc_calls_total", "job": "batch_job", "exporter_job": "batch_exporter"},
|
||||
Value: 25,
|
||||
},
|
||||
model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
|
||||
Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed", "job": "batch_exporter"},
|
||||
Value: 0.0459814091918713,
|
||||
},
|
||||
model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
|
||||
Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar", "job": "batch_exporter"},
|
||||
Value: 78.48563317257356,
|
||||
},
|
||||
model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
|
||||
Metric: model.Metric{"percentile": "0.010000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo", "job": "batch_exporter"},
|
||||
Value: 15.890724674774395,
|
||||
},
|
||||
model.Sample{
|
||||
|
||||
Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
|
||||
Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed", "job": "batch_exporter"},
|
||||
Value: 0.0459814091918713,
|
||||
},
|
||||
model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
|
||||
Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar", "job": "batch_exporter"},
|
||||
Value: 78.48563317257356,
|
||||
},
|
||||
model.Sample{
|
||||
|
||||
Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
|
||||
Metric: model.Metric{"percentile": "0.050000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo", "job": "batch_exporter"},
|
||||
Value: 15.890724674774395,
|
||||
},
|
||||
model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
|
||||
Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed", "job": "batch_exporter"},
|
||||
Value: 0.6120456642749681,
|
||||
},
|
||||
model.Sample{
|
||||
|
||||
Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
|
||||
Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar", "job": "batch_exporter"},
|
||||
Value: 97.31798360385088,
|
||||
},
|
||||
model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
|
||||
Metric: model.Metric{"percentile": "0.500000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo", "job": "batch_exporter"},
|
||||
Value: 84.63044031436561,
|
||||
},
|
||||
model.Sample{
|
||||
|
||||
Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
|
||||
Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed", "job": "batch_exporter"},
|
||||
Value: 1.355915069887731,
|
||||
},
|
||||
model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
|
||||
Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar", "job": "batch_exporter"},
|
||||
Value: 109.89202084295582,
|
||||
},
|
||||
model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
|
||||
Metric: model.Metric{"percentile": "0.900000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo", "job": "batch_exporter"},
|
||||
Value: 160.21100853053224,
|
||||
},
|
||||
model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed"},
|
||||
Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "zed", "job": "batch_exporter"},
|
||||
Value: 1.772733213161236,
|
||||
},
|
||||
model.Sample{
|
||||
|
||||
Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar"},
|
||||
Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "bar", "job": "batch_exporter"},
|
||||
Value: 109.99626121011262,
|
||||
},
|
||||
model.Sample{
|
||||
Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo"},
|
||||
Metric: model.Metric{"percentile": "0.990000", model.MetricNameLabel: "rpc_latency_microseconds", "service": "foo", "job": "batch_exporter"},
|
||||
Value: 172.49828748957728,
|
||||
},
|
||||
},
|
||||
@ -124,9 +129,12 @@ func testProcessor002Process(t test.Tester) {
|
||||
close(c)
|
||||
}(inputChannel)
|
||||
|
||||
reader := strings.NewReader(scenario.in)
|
||||
reader, err := os.Open(path.Join("fixtures", scenario.in))
|
||||
if err != nil {
|
||||
t.Fatalf("%d. couldn't open scenario input file %s: %s", scenario.in, err)
|
||||
}
|
||||
|
||||
err := Processor002.Process(ioutil.NopCloser(reader), time.Now(), model.LabelSet{}, inputChannel)
|
||||
err = Processor002.Process(reader, time.Now(), scenario.baseLabels, inputChannel)
|
||||
if !test.ErrorEqual(scenario.err, err) {
|
||||
t.Errorf("%d. expected err of %s, got %s", i, scenario.err, err)
|
||||
continue
|
||||
|
||||
Loading…
Reference in New Issue
Block a user